Deep learning detects arrhythmia from RR-interval ECG data.
problem Diagnosing arrhythmia using ECG data.
method Convolutional neural network (CNN) on time-sliced RR-interval data.
result Compact system achieves accurate arrhythmia detection.
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3 results for “RR-interval”
Advance Prediction of Ventricular Tachyarrhythmias using Patient Metadata and Multi-Task Networkscs.LG
We describe a novel neural network architecture for the prediction of ventricular tachyarrhythmias. The model receives input features that capture the change in RR intervals and ectopic beats, along with features based on heart rate variability and frequency analysis. Patient age is also included as a trainable embeddi…
Study identifies mental stress in firefighters using heart rate variability data.
problem Unsupervised identification of mental stress in firefighters from heart rate variability data.
method Exploration and comparison of three unsupervised methods: K-Means, convolutional autoencoders, and LSTM autoencoders.
result Convolutional and LSTM autoencoders successfully stratify stressed versus normal samples using HRV markers.